The Potential Roles of Ficus carica Extract in the Management of COVID-19 Viral Infections: A Computer-Aided Drug Design Study.

INTRODUCTION: The conventional processes of drug discovery are too expensive, time-consuming and the success rate is limited. Searching for alternatives that have evident safety and potential efficacy could save money, time and improve the current therapeutic regimen outcomes. METHOD: Clinical phytotherapy implies the use of extracts of natural origin for prophylaxis, treatment, or management of human disorders. In this work, the potential role of common Fig (Ficus carica) in the management of COVID-19 infections has been explored. The antiviral effects of Cyanidin-3-rhamnoglucoside which is abundant in common Figs have been illustrated on COVID-19 targets. The immunomodulatory effect and the ability to ameliorate the cytokine storm associated with coronavirus infections have also been highlighted. This work involves various computational studies to investigate the potential roles of common figs in the management of COVID-19 viral infections. RESULTS: Two molecular docking studies of all active ingredients in common Figs were conducted starting with MOE to provide initial insights, followed by Autodock Vina for further confirmation of the results of the top five compounds with the best docking score. CONCLUSION: Finally, Molecular dynamic simulation alongside MMPBSA calculations were conducted using GROMACS to endorse and validate the entire work.

New thiobarbituric acid scaffold-based small molecules: Synthesis, cytotoxicity, 2D-QSAR, pharmacophore modelling and in-silico ADME screening.

A series of twenty five new thiobarbituric acid derivatives, viz. 3a-h, 4-7, 8a-c, 9, 10a-c, 11 and 12a-d, were designed and synthesized as potential cytotoxic agents. In-vitro screening of the new compounds against the three human cancer cell lines Caco-2, HepG-2 and MCF-7 was performed to assess their intrinsic activity. Compound 12d exhibited potent sub-micromolar activity against HepG-2 and MCF-7 (IC50 = 0.07 and 0.08 µM, respectively). In-silico pharmacophore modelling of this chemotype compounds disclosed a five features' pharmacophore model representing essential steric and electronic fingerprints essential for activity. Finally, a 2D-QSAR model was devised to quantitatively correlate the 2D molecular feature descriptors of this series of thiobarbiturates with their cytotoxic activity against MCF-7. Finally, in silico evaluation of the physicochemical and ADME properties of these derivatives was performed.